convex combination

Kernel-Based Enhanced Oversampling Method for Imbalanced Classification ACML 2025 Relating Misfit to Gain in Weak-to-Strong Generalization Beyond the Squared Loss ICML 2025 The Pivoting Framework: Frank-Wolfe Algorithms with Active Set Size Control AISTATS 2025 Bias Detection via Signaling NeurIPS 2024 Expressive Losses for Verified Robustness via Convex Combinations ICLR 2024 Provably Better Explanations with Optimized Aggregation of Feature Attributions ICML 2024 SubMix: Learning to Mix Graph Sampling Heuristics UAI 2023 Noisy Feature Mixup ICLR 2022 K-shot NAS: Learnable Weight-Sharing for NAS with K-shot Supernets ICML 2021 On InstaHide, Phase Retrieval, and Sparse Matrix Factorization ICLR 2021 On the Convex Combination of Determinantal Point Processes ACML 2021 Safe Reinforcement Learning of Control-Affine Systems with Vertex Networks L4DC 2021 Polytime Decomposition of Generalized Submodular Base Polytopes with Efficient Sampling ACML 2020 Learning Basis Representation to Refine 3D Human Pose Estimations AAAI 2019 Metric Learning as Convex Combinations of Local Models With Generalization Guarantees CVPR 2016 Decontamination of Mutually Contaminated Models AISTATS 2014 Learning Mixtures of Linear Classifiers ICML 2014 Revisiting Stein's Paradox: Multi-Task Averaging JMLR 2014 Multi-Task Averaging NeurIPS 2012 Domain Adaptation with Multiple Sources NeurIPS 2008 Boosting Algorithms for Maximizing the Soft Margin NeurIPS 2007 A PAC-Bayes Risk Bound for General Loss Functions NeurIPS 2006 Generalization Bounds and Complexities Based on Sparsity and Clustering for Convex Combinations of Functions from Random Classes JMLR 2005